Efficacy of cognitive behavioral therapy targeting severe fatigue following COVID-19: results of a randomized controlled trial.

BACKGROUND: Severe fatigue following COVID-19 is prevalent and debilitating. This study investigated the efficacy of cognitive behavioral therapy (CBT) for severe fatigue following COVID-19. METHODS: A multicenter, 2-arm randomized controlled trial was conducted in the Netherlands with patients being severely fatigued 3-12 months following COVID-19. Patients (n = 114) were randomly assigned (1:1) to CBT or care as usual (CAU). CBT, targeting perpetuating factors of fatigue, was provided for 17 weeks. The primary outcome was the overall mean difference between CBT and CAU on the fatigue severity subscale of the Checklist Individual Strength, directly post CBT or CAU (T1), and after six months (T2). Secondary outcomes were differences in proportions of patients meeting criteria for severe and/or chronic fatigue, differences in physical and social functioning, somatic symptoms and problems concentrating between CBT and CAU. RESULTS: Patients were mainly non-hospitalized and self-referred. Patients who received CBT were significantly less severely fatigued across follow-up assessments than patients receiving CAU (-8.8, (95% confidence interval (CI)) -11.9 to -5.8); P < 0.001), representing a medium Cohen's d effect size (0.69). The between-group difference in fatigue severity was present at T1 -9.3 (95% CI -13.3 to -5.3) and T2 -8.4 (95% CI -13.1 to -3.7). All secondary outcomes favored CBT. Eight adverse events were recorded during CBT, and 20 during CAU. No serious adverse events were recorded. CONCLUSIONS: Among patients, who were mainly non-hospitalized and self-referred, CBT was effective in reducing fatigue. The positive effect was sustained at six month follow-up.

Exploring the Impact of Covid-19-Related Perceptions on Psychological Distress and Quality of Life in an International Gastrointestinal Cohort Over Time Guided by the Common Sense Model.

The aim of this longitudinal study was to examine changes in COVID-19 and illness-related perceptions, gastrointestinal symptoms, coping, catastrophising, psychological distress, and QoL during the COVID-19 pandemic. A total of 831 adults with a gastrointestinal condition completed an online questionnaire at baseline (May-October 2020). Of those, 270 (32.5%) participants (85.2% female, mean age = 47.3 years) provided follow-up data (March-May 2021). Repeated-measures multiple analysis of variance and a cross-lagged panel model were used to test the study hypotheses. Gastrointestinal symptoms and COVID-19 perceptions at follow-up were strongly predicted by their baseline values, while illness perceptions were predicted by baseline gastrointestinal symptoms. Cross-lagged relationships indicated a reciprocal relationship between gastrointestinal symptoms and psychological distress. Moreover, gastrointestinal symptoms had substantial predictive utility, strongly predicting future gastrointestinal symptoms, and to a lesser extent, more negative illness perceptions, greater psychological distress, and greater use of adaptive coping strategies across time.

Incidence and impact of anticoagulation-associated abnormal menstrual bleeding in women after venous thromboembolism.

Preliminary data and clinical experience have suggested an increased risk of abnormal uterine bleeding (AUB) in women of reproductive age treated with anticoagulants, but solid data are lacking. The TEAM-VTE study was an international multicenter prospective cohort study in women aged 18 to 50 years diagnosed with acute venous thromboembolism (VTE). Menstrual blood loss was measured by pictorial blood loss assessment charts at baseline for the last menstrual cycle before VTE diagnosis and prospectively for each cycle during 3 to 6 months of follow-up. AUB was defined as an increased score on the pictorial blood loss assessment chart (>100 or >150) or self-reported AUB. AUB-related quality of life (QoL) was assessed at baseline and the end of follow-up using the Menstrual Bleeding Questionnaire. The study was terminated early because of slow recruitment attributable to the COVID-19 pandemic. Of the 98 women, 65 (66%) met at least one of the 3 definitions of AUB during follow-up (95% confidence interval [CI], 57%-75%). AUB occurred in 60% of women (36 of 60) without AUB before VTE diagnosis (new-onset AUB; 95% CI, 47%-71%). Overall, QoL decreased over time, with a mean Menstrual Bleeding Questionnaire score increase of 5.1 points (95% CI, 2.2-7.9), but this decrease in QoL was observed only among women with new-onset AUB. To conclude, 2 of every 3 women who start anticoagulation for acute VTE experience AUB, with a considerable negative impact on QoL. These findings should be a call to action to increase awareness and provide evidence-based strategies to prevent and treat AUB in this setting. This was an academic study registered at www.clinicaltrials.gov as #NCT04748393; no funding was received.

Association of genetic variations in ACE2, TIRAP and factor X with outcomes in COVID-19.

BACKGROUND: Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), can manifest with varying disease severity and mortality. Genetic predisposition influences the clinical course of infectious diseases. We investigated whether genetic polymorphisms in candidate genes ACE2, TIRAP, and factor X are associated with clinical outcomes in COVID-19. METHODS: We conducted a single-centre retrospective cohort study. All patients who visited the emergency department with SARS-CoV-2 infection proven by polymerase chain reaction were included. Single nucleotide polymorphisms in ACE2 (rs2285666), TIRAP (rs8177374) and factor X (rs3211783) were assessed. The outcomes were mortality, respiratory failure and venous thromboembolism. Respiratory failure was defined as the necessity of >5 litres/minute oxygen, high flow nasal oxygen suppletion or mechanical ventilation. RESULTS: Between March and April 2020, 116 patients (35% female, median age 65 [inter quartile range 55-75] years) were included and treated according to the then applicable guidelines. Sixteen patients (14%) died, 44 patients (38%) had respiratory failure of whom 23 required endotracheal intubation for mechanical ventilation, and 20 patients (17%) developed venous thromboembolism. The percentage of TIRAP polymorphism carriers in the survivor group was 28% as compared to 0% in the non-survivor group (p = 0.01, Bonferroni corrected p = 0.02). Genotype distribution of ACE2 and factor X did not differ between survivors and non-survivors. CONCLUSION: This study shows that carriage of TIRAP polymorphism rs8177374 could be associated with a significantly lower mortality in COVID-19. This TIRAP polymorphism may be an important predictor in the outcome of COVID-19.

Longitudinal assessment of the common sense model before and during the COVID-19 pandemic: A large coeliac disease cohort study.

OBJECTIVE: Psychosocial factors likely play a substantial role in the well-being of those living with coeliac disease, especially during the COVID-19 pandemic, however, little research has examined well-being in this cohort using an integrated socio-cognitive model. This study had two aims: (1) Examine changes in gastrointestinal symptoms, psychosocial factors, and well-being outcomes (i.e., psychological distress, quality of life [QoL]) associated with the pandemic, (2) Examine the interrelationship of these variables across timepoints using the Common Sense Model (CSM). METHODS: 1697 adults with coeliac disease (Time 1, pre-pandemic; 83.1% female, mean age = 55.8, SD = 15.0 years) and 674 follow-up participants (Time 2, pandemic; 82.8% female, mean age = 57.0, SD = 14.4 years) completed an online questionnaire. Hypotheses were tested using repeated measures MANOVA and cross-lagged panel model analyses. RESULTS: Participants reported improved QoL, and reduced gastrointestinal symptoms, negative illness perceptions and maladaptive coping from pre-pandemic to during the pandemic. There was no significant change in pain catastrophising or psychological distress. Cross-lagged effects showed gastrointestinal symptoms to predict negative illness perceptions, which in turn were predictive of poorer outcomes across all variables except pain catastrophising. Consistent with the CSM, there was a reciprocal relationship between illness perceptions and QoL over time. Maladaptive coping and pain catastrophising demonstrated limited predictive utility. CONCLUSION: The COVID-19 pandemic appears to have had a small beneficial effect across several indices of well-being among adults with coeliac disease. Cross-lagged relationships highlight illness perceptions as a predictor of well-being outcomes and a potential target for psychosocial interventions.

iWorksafe: Towards Healthy Workplaces During COVID-19 With an Intelligent Phealth App for Industrial Settings

The recent outbreak of the novel Coronavirus Disease (COVID-19) has given rise to diverse health issues due to its high transmission rate and limited treatment options. Almost the whole world, at some point of time, was placed in lock-down in an attempt to stop the spread of the virus, with resulting psychological and economic sequela. As countries start to ease lock-down measures and reopen industries, ensuring a healthy workplace for employees has become imperative. Thus, this paper presents a mobile app-based intelligent portable healthcare (pHealth) tool, called i WorkSafe, to assist industries in detecting possible suspects for COVID-19 infection among their employees who may need primary care. Developed mainly for low-end Android devices, the i WorkSafe app hosts a fuzzy neural network model that integrates data of employees' health status from the industry's database, proximity and contact tracing data from the mobile devices, and user-reported COVID-19 self-test data. Using the built-in Bluetooth low energy sensing technology and K Nearest Neighbor and K-means techniques, the app is capable of tracking users' proximity and trace contact with other employees. Additionally, it uses a logistic regression model to calculate the COVID-19 self-test score and a Bayesian Decision Tree model for checking real-time health condition from an intelligent e-health platform for further clinical attention of the employees. Rolled out in an apparel factory on 12 employees as a test case, the pHealth tool generates an alert to maintain social distancing among employees inside the industry. In addition, the app helps employees to estimate risk with possible COVID-19 infection based on the collected data and found that the score is effective in estimating personal health condition of the app user.

COVID-19 Vaccine Candidates: Prediction and Validation of 174 SARS-CoV-2 Epitopes (preprint)

The recent outbreak of SARS-CoV-2 (2019-nCoV) virus has highlighted the need for fast and efficacious vaccine development. Stimulation of a proper immune response that leads to protection is highly dependent on presentation of epitopes to circulating T-cells via the HLA complex. SARS-CoV-2 is a large RNA virus and testing of all overlapping peptides in vitro to deconvolute an immune response is not feasible. Therefore HLA-binding prediction tools are often used to narrow down the number of peptides to test. We tested 19 epitope-HLA-binding prediction tools, and using an in vitro peptide MHC stability assay, we assessed 777 peptides that were predicted to be good binders across 11 MHC allotypes. In this investigation of potential SARS-CoV-2 epitopes we found that current prediction tools vary in performance when assessing binding stability, and they are highly dependent on the MHC allotype in question. Designing a COVID-19 vaccine where only a few epitope targets are included is therefore a very challenging task. Here, we present 174 SARS-CoV-2 epitopes with high prediction binding scores, validated to bind stably to 11 HLA allotypes. Our findings may contribute to the design of an efficacious vaccine against COVID-19.